Lead Site Reliability Engineer - Operations Excellence for AI Platforms
Salary not listed • Plano, TX, United States • Full-time
Posted 1mo ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability. As a Lead Site Reliability Engineer within the AI Machine Learning and Data platform team, you will hold a leadership role, demonstrate strong knowledge across multiple technical domains, and advise others on technical and business issues. You will take the lead in conducting resiliency design reviews, break down complex problems into digestible work for other engineers, act as a technical lead for medium to large-sized products, and provide advice and mentoring to other engineers.
Responsibilities
- Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications.
- Partner with product engineering teams to ensure AI/ML systems are reliable and high-performing.
- Develop observability, security, automation, and fin-ops tools and orchestration.
- Provide strategic technology leadership by defining and evaluating standards and architecture for reliability, observability, and automation frameworks.
- Build strong cross-functional relationships to foster engagements across the organization and deliver solutions.
- Debug and solve issues in a production environment, identify root cause, and remediate.
- Participate in on-call rotations, incident management, and escalation workflows.
- Take full ownership of problems, develop solutions, and acquire new knowledge.
- Mentor and guide junior engineers.
- Use enterprise-authorized AI capabilities to accelerate major-incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data securely.
- Lead reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices, ensuring traceability, resiliency, and security controls.
Requirements
- Formal training or certification on site reliability engineering concepts and 5+ years of applied experience.
- Expertise in SRE principles, reliability, scalability, and performance of applications and infrastructure.
- Expertise in programming with Python and Infrastructure as Code tools like Terraform.
- Demonstrable experience using enterprise-authorized AI capabilities to improve SRE workflows, with strong validation habits and awareness of data sensitivity.
- Ability to evaluate AI-assisted operational recommendations for correctness and risk, define guardrails for team usage, and ensure outcomes align with resiliency and security expectations.
- Experience in architecting distributed systems and cloud-native architecture in AWS.
- Systematic problem-solving and troubleshooting skills in complex systems.
- Excellent communication skills and ability to represent and present business and technical concepts to stakeholders.